Triple
T2584747
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Clarendon, Arlington |
E57171
|
entity |
| Predicate | pedestrianInfrastructure |
P25669
|
FINISHED |
| Object | sidewalks and crosswalks |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: sidewalks and crosswalks | Statement: [Clarendon, Arlington, pedestrianInfrastructure, sidewalks and crosswalks]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: pedestrianInfrastructure Context triple: [Clarendon, Arlington, pedestrianInfrastructure, sidewalks and crosswalks]
-
A.
pedestrianFriendly
Indicates that an environment, route, or area is designed or suitable for safe, comfortable, and convenient use by pedestrians.
-
B.
hasPedestrianAccessTo
chosen
Indicates that a location or area can be reached or entered safely and directly by people on foot.
-
C.
pedestrianActivity
Indicates that an entity is engaged in or associated with walking or other on-foot movement or behavior.
-
D.
pedestrianOnly
Indicates that a path, area, or route is designated exclusively for pedestrians and prohibits vehicle access.
-
E.
pedestrianRestrictions
Indicates that there are specific rules or limitations governing where or how pedestrians may travel or access an area.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69ab4a4dca6481908c301f8e317396e7 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd3cd07588190b3cb8cc348f12938 |
completed | March 7, 2026, 7:29 a.m. |
| PD | Predicate disambiguation | batch_69abd0d19308819089ee942513d567a4 |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:49 p.m.